Imaging refers to the process of acquiring data about some mass and inferring from the data a representation of the mass. Imaging is useful for a variety of applications. One example includes displaying subsurface structures of the earth by gathering seismic data. Another example is displaying structures within human bodies through the use of ultrasound. Imaging is also useful for creating images of a mass that has been analyzed by radar, sonar, and other types of remote sensing technologies.
All of the possible uses for imaging require data intensive calculations. When an image of a mass is created, the quality of the image is dependent upon the amount of data that is acquired. The acquired data must be processed by some type of algorithm, depending upon the nature of the data and the type of image to be generated. With potentially millions or billions of data values, performing even a simple algorithm on a conventional computer system can take a long period of time. In certain instances, the amount of time to process the image can be so great that the mass analyzed may change before the image can be created. Typically, processing time is slightly reduced by lowering the resolution of the data, which then decreases the accuracy of the resulting image.
These problems are particularly apparent when imaging geological subsurface structures. When imaging a subsurface structure, the mass to be analyzed is broken down into millions of individual points. Seismic energy reflections from the points are recorded on the surface, and the imaging system must determine each individual point's energy contribution. Using state of the art computers, this process can take several months. This length of time is troublesome because the substructure may change before the imaging can be completed. Lowering the resolution decreases the reliability of the image. This lack of reliability is also troublesome because these images may be used by the oil industry to determine the location and size of natural oil reservoirs. The proper drilling location is critical to the successful depletion of the reservoir, and an accurate image is necessary. Thus, the oil industry would benefit from a computer architecture capable of producing an accurate image in a shorter amount of time.